Autonomous optimization for query speed, cost, and table health — across tables and engines. Start free in minutes.
Production benchmarks
Open and runs on your stack
LakeOps| Operation | Table | Duration | Impact | Time | Status |
|---|---|---|---|---|---|
| Compact Data Files | customer_orders orders | 4s | 1.24 TB, 16 → 1 files | 57 minutes ago | SUCCESS |
| Expire Snapshots | payment_transactions payments | 27s | 8.2 TB | 4 hours ago | SUCCESS |
| Expire Snapshots | inventory_snapshots_20250702 warehouse | 3s | 2.1 TB | 4 hours ago | SUCCESS |
| Rewrite Manifests | raw_clickstream analytics | 1.9s | 3 → 1 manifests | 5 hours ago | SUCCESS |
| Compact Data Files | product_catalog products | 6m 11.3s | 3,008 → 1,256 files | 6 hours ago | SUCCESS |
Intelligent Control Plane
Connect in 10 minutes. Your lakehouse autonomously optimizes for performance, cost, and health — across every table and engine.
| Table | NS | Size | Status |
|---|---|---|---|
| customer_orders | orders | 1.24 TB | HEALTHY |
| payment_transactions | payments | 860 GB | WARNING |
| raw_clickstream | analytics | 4.6 TB | CRITICAL |
| product_catalog | products | 42 GB | HEALTHY |
| user_sessions | analytics | 1.9 TB | WARNING |
| inventory_levels | operations | 320 GB | HEALTHY |
| shipping_events | logistics | 580 GB | HEALTHY |
| search_query_logs | analytics | 3.2 TB | CRITICAL |
Learns from query patterns and table signals to decide what to optimize, when, and how — no schedules, no manual tuning.
Results
Benchmarks from production-grade tables across multiple engines and clouds.
Query speed
After compaction + layout optimization
CPU reduction
Compute hours across all engines
Storage saved
Orphans, snapshots & bloat removed
Table health
Autonomous maintenance keeps every table optimized
Only metadata is processed — never retained or stored.
Telemetry reveals table health and actions needed.
Autopilot, manual approval, or policy-driven.
See It In Action
Catalog connection, autonomous maintenance, compaction, routing, and governance — in one walkthrough.
SOC 2, SSO, RBAC, dedicated support, and the scale your largest Iceberg lakes demand.
SOC 2 Type II, encryption, SSO/RBAC, and audit trails for regulated teams.
One control plane for your full lake. Real-time visibility, policies, and predictable performance.
Dedicated onboarding, training, and enterprise SLAs. Deploy in VPC or on-prem.
Testimonials
LakeOps took the pain out of compaction and maintenance. We went from ad-hoc scripts and firefighting to a single control plane. Query performance improved and our platform team finally has visibility across the lake.
We evaluated several options for Iceberg operations. LakeOps stood out for its focus on automation and multi-engine support. Deployment was straightforward and the impact on cost and latency was measurable within weeks.
Resources
Iceberg tables degrade silently — small files pile up, snapshots bloat metadata, and query latency creeps higher. A breakdown of the nine components every production data lake needs to stay healthy.
Netflix spent years building an intelligent lakehouse — Polaris, Autotune, janitors, and Metacat. LakeOps lets every team build the same — and go beyond — in minutes.
A data lakehouse control plane is the automated operational intelligence layer on top of your lakehouse infrastructure — providing full observability, governance, and control while continuously maintaining and optimizing every Iceberg table and query engine for performance and cost, without vendor lock-in.
Get Started
Get a personalized walkthrough with your data and architecture.
Short call, no commitment.
Typically 30 min · Free
